Haplotype Data Structure for Nucleotide Read Alignment
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Solution Overview
Problem
Existing nucleobase sequencing platforms and data analysis software often utilize reference genomes that misrepresent certain populations, leading to inaccurate read alignment and variant calling due to the use of linear genomes based on limited individual samples and graph reference genomes that consume excessive memory and computing resources with redundant alternate paths, causing misalignment and reduced mapping quality.
Innovation Solution
A read alignment adjustment system utilizing a haplotype data structure that encodes allele-variant differences to determine alignments by partitioning the reference genome into bins, allowing for efficient scoring of candidate alignments without directly aligning to alternate sequences, thereby improving computing speed and accuracy by adjusting alignment scores based on population haplotype variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If graph reference genomes with multiple alternate contiguous sequences are used to represent population haplotypes, then genetic representation accuracy is improved, but memory consumption and computing resources increase excessively
Solution Approach 1:
The patent extracts only the essential variant information (allele-variant differences) from complete alternate contiguous sequences, storing merely the differences rather than full sequences. This extraction approach maintains population haplotype representation accuracy while dramatically reducing memory consumption by eliminating redundant reference nucleobases.
Solution Approach 2:
Instead of storing complete alternate sequences and comparing reads against them, the patent inverts the approach by storing only the differences from a primary contiguous sequence and applying these differences to adjust alignment scores. This inversion reduces the data volume from countless full sequences to compact difference representations.
2Adaptability or versatility
If graph reference genomes with numerous alternate contiguous sequences are used to account for population variations, then mapping comprehensiveness is improved, but computer processing time increases
Solution Approach 1:
The patent performs preliminary action by pre-processing and encoding allele-variant differences from population haplotypes into a compact data structure before alignment. This pre-computed difference information is then quickly applied during read alignment to adjust scores, avoiding the time-consuming process of navigating countless alternate sequences during actual mapping operations.
Solution Approach 2:
The patent changes the parameter representation from complete sequences to difference encodings (allele-variant differences). This parameter transformation compresses the data representation, allowing comprehensive population haplotype coverage to be maintained while reducing processing time through more efficient data access and comparison during alignment scoring.
3Measurement precision
If excessive seed extensions are used to locate unique matches in graph reference genomes, then alignment specificity is improved, but mapping sensitivity decreases
Solution Approach 1:
The patent applies local quality by using the allele-variant difference information to locally adjust alignment scores at specific genomic regions where population haplotypes differ from the primary sequence. This localized score adjustment maintains high alignment specificity in variant regions while preserving mapping sensitivity overall, avoiding the need for excessive seed extensions that would reduce sensitivity.
Data Source
AI summary
This disclosure describes methods, non-transitory computer readable media, and systems that implement improved mapping and alignment of nucleotide reads with genomic regions of a reference genome. For instance, the disclosed systems can identify, for one or more candidate alignments between nucleotide reads from a genomic sample with a primary contiguous sequence at respective genomic regions of a reference genome, allele-variant differences between the primary contiguous sequence and population haplotypes within the respective genomic regions to generate alignment score adjustments for each population haplotype. To facilitate the disclosed methods for improved mapping and alignment of nucleotide reads, the disclosed systems can utilize a haplotype data structure comprising a hierarchical partitioning of a reference genome into reference bins representing respective genomic regions and encoding region-specific allele-variant differences between population haplotypes and a primary contiguous sequence of the reference genome.